Automotive engineering is a relatively new technological field, especially for car driving. Autonomous car driving (also so called driverless car, self-driving car, robotic car) is associated with vehicles that are capable of sensing its environment and navigating without human input. Autonomous vehicles are capable of detecting surroundings using radar, LIDAR (measuring device to measure distances by means of laser light), GPS (Global Positioning System), odometry (measuring device for measuring changings in position over time by means of using motion sensor data), and computer vision. In autonomous cars, advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Autonomous cars have control systems that are capable of analyzing sensory data to distinguish between different cars on the road, which is very useful in planning a path to the desired destination. Early trials for autonomous car driving systems date back to the 1920s and 30s. However, the first self-sufficient (i.e., truly autonomous) cars appeared in the 1980s, with Carnegie Mellon University's Navlab and ALV projects in 1984 and Mercedes-Benz and Bundeswehr University Munich's Eureka Prometheus Project in 1987. Since then, numerous major companies and research organizations have developed working prototype autonomous vehicles. Recently, Tesla Motors has pushed driverless car technology with its autopilot system. Most previous systems required the driver to maintain hands on the steering wheel whereas Tesla allows for periods of time without. Another upcoming system is Cadillac's super cruise that will not require the driver to maintain hands on the wheel. An overview of the development is given by FIG. 1.
Apart from autonomous car driving, automotive engineering is, in fact, more common for aerospace engineering and marine engineering, than for vehicle engineering. Though, automotive engineering comprises similar technical means in the different fields, it does not completely overlap. Automotive car engineering comprises elements of mechanical, electrical, electronic, software and safety engineering as applied to the design, manufacture and operation of motorcycles, automobiles and trucks and their respective engineering subsystems. One important aspect of automotive engineering is related to safety engineering: Safety engineering is the assessment of various crash scenarios and their impact on the vehicle occupants. These are tested against very stringent regulatory or governmental regulations. Some of these requirements include: seat belt and air bag functionality testing, front and side impact testing, and tests of rollover resistance. Assessments are done with various methods and tools, including computer crash simulation (typically finite element analysis), crash test dummies, and partial system sled and full vehicle crashes. Other important aspects of automotive engineering relate, for example, to (i) fuel economy/emissions optimization systems, (ii) vehicle dynamics optimization (vehicle dynamics is the vehicle's response of attributes as e.g. ride, handling, steering, braking, comfort and traction), (iii) NVH (noise, vibration, and harshness) engineering (i.e. the customer's feedback systems both tactile (felt) and audible (heard)) from the vehicle, (iv) vehicle electronics engineering, in particular automotive electronics engineering, which systems are responsible for operational controls such as the throttle, brake and steering controls; as well as comfort and convenience systems such as the HVAC (heating, ventilating, and air conditioning) systems, infotainment systems, and lighting systems. Automotive systems with modern safety and fuel economy requirements are not possible without electronic controls, (v) performance control system (e.g. how quickly a car can accelerate (e.g. standing start 100 m elapsed time, 0-100 km/h, etc.), top speed, how short and quickly a car can come to a complete stop from a set speed (e.g. 50-0 km/h), how much g-force a car can generate without losing grip, recorded lap times, cornering speed, brake fade, or the amount of control in inclement weather (snow, ice, rain)), (vi) shift quality systems (driveline, suspension, engine and power-train mounts, etc.), (vii) durability and corrosion engineering including controls under mileage accumulation, severe driving conditions, and corrosive salt baths etc., (viii) package/ergonomics engineering, as occupant's access to the steering wheel, pedals, and other driver/passenger controls, (ix) climate control, as windshield defrosting or heating and cooling capacity, (x) Drivability engineering as e.g. the vehicle's response to general driving conditions, e.g. cold starts and stalls, RPM (revolutions per minute) dips, idle response, launch hesitations and stumbles, and performance levels etc., (xi) quality control engineering, as e.g. systems to minimize risks related to product failures and liability claims of automotive electric and electronic systems etc. Finally, an important aspect of autonomous vehicle driving typically relates to modern telematics means and systems. In electronic, telecommunication and insurance industry, the technology is adopting similar and consistent technical strategies to improve the effectiveness of interactions with mobile systems and devices, but also with the customer or user of those systems, which today increasingly is a pure technology component. Further, social networking, telematics, service-oriented architectures (SOA) and usage-based services (UBS) are all in interacting and pushing this development. Social platforms, as e.g. Facebook, Twitter and YouTube, offer the ability to improve customer interactions and communicate product information. However, the field of telematics is larger still, as it introduces entirely new possibilities that align the technical input requirements and problem specifications of dynamic risk-transfer, technology and mobility. SOA and telematics is becoming key to managing the complexity of integrating known technologies and new applications.
As mentioned above, autonomous vehicle electronics engineering, which systems are responsible for operational controls of the vehicle such as the throttle, brake controls, steering controls, and lighting systems, is one of the key technologies in automotive car driven. Automotive systems with modern steering, safety and fuel economy requirements are not possible without appropriate electronic controls. Typically, the use of telematics means constitutes a central part of the autonomous vehicle electronics engineering. Telematics, in the context of autonomous car driving, comprises telecommunications, vehicular technologies, road transportation, road safety, electrical engineering (sensors, instrumentation, wireless communications, etc.), and information technology (multimedia, Internet, etc.). Thus, also the technical field of telematics are affected by a wide range of technologies as the technology of sending, receiving and storing information via telecommunication devices in conjunction with affecting control on remote objects, the integrated use of telecommunications and informatics for application in vehicles and e.g. with control of vehicles on the move, GNSS (Global Navigation Satellite System) technology integrated with computers and mobile communications technology in automotive navigation systems. The use of such technology together with road vehicles is also called vehicle telematics. In particular, telematics triggers the integration of mobile communications, vehicle monitoring systems and location technology by allowing a new way of capturing and monitoring real-time data. Usage-based risk-transfer systems, as e.g. provided by the so called Snapshot technology of the firm Progressive, links risk-transfer compensation or premiums to monitored driving behavior and usage information gathered by an in-car telematics device. In relation to automotive car systems, telematics typically further comprises installing or embedding telecommunications devices mostly in mobile units, as e.g. cars or other vehicles, to transmit real-time driving data, which for example can be used by third parties' system, as automated risk-monitoring and risk-transfer systems, providing the needed input e.g. to measure the quality and risks, to which the vehicle is exposed to. Various telematics instruments are available in the market, as e.g. vehicle tracking and global positioning satellite system (GPS) technologies or telecommunications devices that allow to be connected from almost anywhere. In particular, dynamically monitored and adapted risk-transfer could be imaginable by interconnecting telematics of the autonomous car driving system with other real-time measuring systems. After getting involved into a car accident, emergency and road services could be automatically activated, vehicle damage assessed, and the nearest repair shop contacted. In summary, the traditional operability of risk-transfer systems and insurance coverage could be transformed to real-time navigation and monitoring, including the automated activation of concierge service, safe driving tips, video-on-demand for the kids in the backseat, in-car or online feedback, and real-time vehicle diagnostics.
In addition to real-time surveillance, it is to be mentioned, that an insurance agent may want to exchange information with a customer associated with insurer for a number of different reasons. However, the information exchange between the customer and the insurer and/or the insurer and the reinsurer mostly is still cumbersome and time-consuming, and thus, risk-transfers provided by such structures typically remain static within a fixed time period agreed upon. For example, an existing or potential consumer may access an insurance agent's web page to determine a yearly or monthly cost of an insurance policy (e.g. hoping to save money or increase a level of protection by selecting a new insurance company). The consumer may provide basic information to the insurance agent (e.g. name, a type of business, date of birth, occupation, etc.), and the insurance agent may use this information to request a premium quote from the insurer. In some cases, the insurer will simply respond to the insurance agent with a premium quote. In other cases, however, an underwriter associated with insurer will ask the insurance agent to provide additional information so that an appropriate premium quote can be generated. For example, an underwriter might ask the insurance agent to indicate how often, where and to which time a motor vehicle is mainly used or other data as age of the motor vehicle and indented use (transportation etc.). Only after such additional information is determined, an appropriate risk analysis can be performed by the insurer to process adapted underwriting decision, and/or premium pricing.
Autonomous car driving with integrated telematics may offer new technological fields, in particular in monitoring and steering by means of centralized expert systems, as e.g. in the risk-transfer technology far more accurate and profitable pricing models provided by such automated expert systems. This would create a huge advantage, in particular for real-time and/or usage-based and/or dynamically operated systems. The advantage of such autonomous car driving systems is not restricted to risk transfer rather as also advantages e.g. in fleets' management that reduce fuel consumption and improve safety etc. etc. Other fields may also benefit from such autonomous car driving systems, as state and local governments needs striving to improve fuel consumption, emissions and highway safety. Some states, for example, recently issued dynamic pay-as-you-drive (PAYD) regulations, which on the other side allows insurers to offer drivers insurance rates based on actual versus estimated miles driven. It's a financial incentive to drive less.